Avtech Scientific announces the first open source release of its Advanced Simulation Library. The software will be distributed under the free GNU Affero General Public License (AGPLv3) with an optional commercial license. The company hopes that this step will encourage collaboration with the user community accelerating the extension of ASL and lead to sustaining of its high quality standards. Following the release Avtech Scientific is looking for partners among embedded systems vendors (FPGA, DSP) and GPU/APU manufacturers to bring its innovative technology to new hardware platforms.
Advanced Simulation Library is a free and open source hardware accelerated multiphysics simulation platform (and an extensible general purpose tool for solving Partial Differential Equations). Its computational engine is written in OpenCL and utilizes matrix-free solution techniques which enable extraordinarily high performance, memory efficiency and deployability on a variety of massively parallel architectures, ranging from inexpensive FPGAs, DSPs and GPUs up to heterogeneous clusters and supercomputers. The engine is hidden entirely behind simple C++ classes, so that no OpenCL knowledge is required from application programmers. Mesh-free, immersed boundary approach allows one to move from CAD directly to simulation drastically reducing pre-processing efforts and amount of potential errors. ASL can be used to model various coupled physical and chemical phenomena and employed in a multitude of fields: computational fluid dynamics, virtual sensing1, industrial process data validation and reconciliation, image-guided surgery, computer-aided engineering, design space exploration, crystallography, etc..
Virtual or soft sensors are applications for simulation-based monitoring and control of industrial processes, used to provide feasible and economical alternatives to hardware sensors if the latter are unavailable, impractical or do not provide sufficient information. Virtual sensors are often deployed on embedded systems but can also run on more powerful hardware depending on the complexity of the underlying model and operational needs. ↩